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Enregistrement W4386245926 · doi:10.1093/eurheartj/ehad537

Incorporating principles from commercial advertising into cardiovascular health promotion efforts

2023· article· en· W4386245926 sur OpenAlexaff
David J.T. Campbell, Raj Pannu, Braden Manns

Notice bibliographique

RevueEuropean Heart Journal · 2023
Typearticle
Langueen
DomainePharmacology, Toxicology and Pharmaceutics
ThématiquePharmaceutical industry and healthcare
Établissements canadiensLibin Cardiovascular Institute of AlbertaUniversity of Calgary
Organismes subventionnairesnon disponible
Mots-clésMedicineCardiovascular healthHealth promotionPromotion (chess)AdvertisingPublic healthInternal medicineNursingDisease

Résumé

récupéré en direct d'OpenAlex

Given that cardiovascular disease (CVD) remains a leading cause of mortality, the importance of preventing cardiovascular events is critical for patients and healthcare systems. Individual health behaviours play an important role in an individual’s CVD risk and trajectory. Unfortunately, health behaviours are difficult to influence, despite many different types of programmes for providing health education and behaviour change counselling. Due to the underwhelming mixed successes of traditional educational programmes,1 there is a need for novel approaches to promoting the adoption of healthy behaviours to minimize individual risk while maximizing population health. We recently published the findings from the Assessing outcomes of enhanced Chronic disease Care through patient Education and a value-baSed formulary Study (ACCESS), demonstrating that a novel approach to education and self-management was associated with significant improvements in cardiovascular outcomes.2 We tested a self-management education and support (SMES) programme that incorporated principles of commercial advertising and demonstrated a 22% reduction in the primary outcome (a composite of mortality, major adverse cardiovascular events, revascularization, and cardiovascular-related hospitalizations). The findings were driven by a 34% reduction in the rate of hospitalizations, 68% of which were for heart failure. While this is encouraging, the mechanism of benefit was unclear, as the only intermediate outcome that was significantly affected by the intervention was the number of participants who received a statin prescription. Despite our prior qualitative and quantitative process evaluations of this programme,3–5 further research into the mechanism of benefit and how to maximize its effect is required. Consumer advertising refers to creative communications tactics directed towards individuals and families intended to influence behaviour of the target audience. Studies on the effect of advertising in health have found that it can empower and engage patients through increasing disease awareness, medication adherence, and the strengthening of physician–patient relationships.6 There are also well-described harms of direct-to-consumer advertising in medicine.7 Despite this, we hypothesized that with sufficient medical oversight, communications based on advertising principles could be harnessed to benefit patients and health systems, specifically in the context of chronic disease management where daily behaviour is a key driver of adverse events. Advertisers create engaging communications using a strategic framework that is focused on the psychology, behaviours, and habits of the intended recipient. The framework is conceptually very simple, consisting of a research phase, a creative phase, and an execution phase. In the research phase, a conventional approach that is often used is the 5 Cs: customer, category, company, culture, and connectivity. ‘Customer’ refers to the advertising target audience, who is defined both demographically and psychographically with respect to the intended behaviour; ‘category’ refers to the competitive set: the products, services, cultural, and behavioural obstacles that compete with the intended action; ‘company’ is the marketer and its perceived advantages and disadvantages in the eyes of the target audience; ‘culture’ are the broad societal concepts that shape the target audiences’ mind and habits relating to the subject area; and ‘connectivity’ refers to the media channels most often used by the intended audience. Polling, focus groups, and human-centred ethnographic research are used to inform the overall strategy. In the creative phase, data from the research phase is synthesized and distilled into ‘brand concepts’. The brand concepts are tested with audiences, refined, and reduced to a singular idea that serves as the central story of the ‘brand’. During this phase, the ‘brand personality’, which describes the ‘look and feel’ of the brand, is also built. In the execution phase, branded materials that are true to the brand story and are in the form that is most trusted by the intended target audience are created and disseminated. In the case of creating the SMES content for the ACCESS trial, this process was closely followed (Figure 1). The research phase provided key insights into the psychological state of the audience, their preferred modes of communication, their aspirations for their lives, and their relationship with their own health and the healthcare system. These insights led to the brand position: ‘living a healthy life on my own terms’. The name ‘Moxie’, which came out of research testing, is a word that both means and inspires confidence. The ‘stickiness’ of the Moxie approach relied on four essential features: the Moxie brand was coming from the university hospital system, a trusted source of medical information; each individual piece of branded material relied heavily on storytelling and design and minimally on disease education; and all the information that each participant received was directly applicable and tailored to their own specific medical conditions, providing no extraneous information that was not pertinent; finally, the reliance on mailers was intentional and based on the stated preference over electronic communications. The overall Moxie programme, therefore, was created using the principles of advertising and intentionally designed with the psychosocial circumstances of the audience at its centre. Process of developing MOXIE using principles from commercial advertising One of the major advantages of this advertising-based approach to providing health education is its scalability. Once the intervention materials are developed and tailoring criteria are decided upon, the intervention could be rolled out to entire populations with relatively minimal incremental costs. Based on our calculations, if Moxie had been rolled out to 10 000 individuals (rather than 2380 as within the trial), the cost per recipient would have been as low as $250 (compared to $540) for the 3-year period.2 This contrasts with the current standard which often relies upon in-person provision of education either in group or one-on-one settings. This requires hiring a trained facilitator or educator, who is, in many cases, a highly trained healthcare professional—dietitian, nurse, or pharmacist. For the equivalent cost of the ACCESS intervention, a health system might be able to purchase a single education session with such personnel. This is important to note as most of the studies demonstrating the effectiveness of motivational interviewing for behaviour change require multiple sessions.8 This is not to say that there would not be a role for health educators, but their role could be focused upon providing patient-specific advice such as insulin dosing or medication titration, whereas more generic information could be efficiently provided by a remote and standardized SMES programme like Moxie. Based upon the findings of the ACCESS trial, we encourage health systems to consider how incorporating principles from corporate advertising can help accomplish objectives of reducing avoidable hospitalizations by improving population health through behaviour change for cardiovascular prevention. R.P. is the CEO of Emergence Creative, the social impact creative design agency that created Moxie.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,013
score de la tête « metaresearch » (Gemma)0,017
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,013
Score d'incertitude au seuil0,068

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0130,017
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0010,002
Communication savante0,0030,002
Science ouverte0,0010,002
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0070,001

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,570
Tête enseignante GPT0,538
Écart entre enseignants0,031 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2023
Routes d'admission1
Résumé présentoui

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